Improved key rate bounds for practical decoy-state quantum key distribution systems

TL;DR

This paper introduces a tighter statistical fluctuation bound for practical decoy-state quantum key distribution, significantly improving key rate estimates and maximum secure distance by reducing failure probability and optimizing system parameters.

Contribution

It develops a more rigorous and tighter bound for the decoy-state method, nearly closing the gap with Gaussian approximation techniques and enhancing practical QKD performance.

Findings

Higher secret key rates achieved

Increased maximum secure distance

Almost closes gap between fluctuation analysis methods

Abstract

The decoy-state scheme is the most widely implemented quantum key distribution protocol in practice. In order to account for the finite-size key effects on the achievable secret key generation rate, a rigorous statistical fluctuation analysis is required. Originally, a heuristic Gaussian-approximation technique was used for this purpose, which, despite of its analytical convenience, was not sufficiently rigorous. The fluctuation analysis has recently been made rigorous by using the Chernoff bound. There is a considerable gap, however, between the key rate bounds obtained from these new techniques and that obtained from the Gaussian assumption. Here, we develop a tighter bound for the decoy-state method, which yields a smaller failure probability. This improvement results in a higher key rate and increases the maximum distance over which secure key exchange is possible. By optimizing the system parameters, our simulation results show that our new method almost closes the gap between the two previously proposed techniques and achieves a similar performance to that of conventional Gaussian approximations.